For years, brands
have relied on an arsenal of tools to hear customer feedback. Surveys. Social listening. Focus groups. Ethnographic studies. From those and many other sources, businesses have been able to build a
comprehensive understanding of customer wants and needs, enabling them to create more effective products and marketing strategies.
Now, businesses are entering a new frontier with AI. The
adoption of AI (including generative AI) opens up new ways for companies to understand customers by applying advanced data analysis, real-time insights, and personalized interactions. It’s all
very exciting – but not without risk.
Let’s take a closer look.
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At the heart of a typical marketing campaign is the
customer persona: a detailed, semi-fictional representation of a business’s ideal customer based on market research and real-world data about existing customers. AI turns these personas into
always-on personas, which are dynamic representations that continuously evolve based on real-time data and interactions.
Always-on personas are special because they provide continuous,
real-time insights and feedback, allowing brands to adapt rapidly to changing consumer preferences and market conditions. These AI-generated personas are constantly updated with new data inputs,
ensuring they reflect the most current consumer behaviors and preferences.
P&G employs AI-driven personas to understand consumer behavior better and personalize marketing campaigns.
This helps the company tailor its advertising and product offerings to meet the specific needs and preferences of different customer segments.
LEGO famously collaborates with customers by giving them a sandbox to share ideas for new designs. Generative AI makes that process faster and more
iterative. Coca-Cola’s Real Magic initiative uses consumer-facing generative AI to enhance its marketing efforts. The company partnered with OpenAI to create a custom site where users can
generate AI-infused images using Coca-Cola’s iconic brand elements. This technology, built on OpenAI’s DALL-E 3 image creation platform, was trained to understand and replicate
Coca-Cola’s distinct features, such as its signature script and specific shade of red. Through this interactive platform, consumers input prompts to receive personalized images, effectively
turning every user interaction into a learning opportunity for the AI model. This continuous engagement allows Coca-Cola to use the AI as a vast, ongoing focus group, gathering valuable insights and
refining its marketing strategies based on real-time consumer feedback.
Coca-Cola is not alone. Many other businesses are leaning into AI to learn from customer feedback in real time. For
example, Stitch Fix uses generative AI to assist its stylists in interpreting customer feedback and providing personalized product recommendations. This application of AI helps the company better
understand and meet individual customer preferences, thereby improving the overall customer experience.
AI enables businesses to
process and act upon vast amounts of customer data in real-time, creating highly personalized experiences for millions of customers simultaneously. This level of hyper-personalization at scale, with
continuous optimization and cross-channel consistency, is simply not feasible without the power of AI.
For instance, Michaels Stores has used generative AI to enhance customer engagement through
hyper-personalization. The company developed a content generation and decision-making platform that significantly increased the personalization of their email campaigns from 20% to 95%. This change
led to a 41% increase in click-through rates for SMS campaigns and a 25% increase for email campaigns.
Learning From Customer Service
Chatbots are more than
customer service tools. With AI, they provide a 24/7 customer feedback loop that businesses can use to become more responsive. With GenAI, chatbots can understand their customers by using language
understanding, sentiment analysis, personalization, and predictive analytics. Every interaction with a generative AI chatbot provides valuable data on customer preferences, pain
points, and behavior patterns. By analyzing this data, businesses can gain deeper insights into their target audience, refine their marketing strategies, and develop more effective products and
services.
For instance, Delta Airlines’ “Ask Delta” virtual assistant exemplifies how generative AI chatbots gather valuable data
from every interaction. By analyzing customer questions, preferences, and pain points, Delta gains insights into its target audience, enabling the company to refine marketing
strategies, improve customer experiences, and develop products and services that better meet customer needs. This continuous feedback loop demonstrates the power of generative AI
chatbots in driving data-driven decision-making and improving customer satisfaction in the airline industry.
Here’s the catch: to realize the benefits of
AI, you’ll probably need to build your own in-house large language model. The off-the-shelf tools such as ChatGPT have a fundamental drawback: they are running out of publicly available data to
train themselves to get better. Epoch AI estimates that the stock of human-generated public text, around 300 trillion tokens, might be fully utilized between 2026 and 2032. This timeline could be
accelerated if models are intensely overtrained.
But the upside to developing your own marketing LLM? You tap into your private first-party data to create more valuable insights than you can get
from an off-the-shelf tool. Invest wisely.